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Video Frame Interpolation On Snu Film Extreme
Metrics
PSNR
SSIM
Results
Performance results of various models on this benchmark
| Paper Title | Repository | |||
|---|---|---|---|---|
| DBVI | 25.90 | 0.876 | Deep Bayesian Video Frame Interpolation | - |
| ST-MFNet | 25.81 | - | ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation | |
| VFIMamba | 25.79 | 0.8682 | VFIMamba: Video Frame Interpolation with State Space Models | |
| EMA-VFI | 25.69 | 0.8661 | Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation | |
| UPR-Net LARGE | 25.63 | 0.8641 | A Unified Pyramid Recurrent Network for Video Frame Interpolation | |
| DQBC | 25.61 | 0.8648 | Video Frame Interpolation with Densely Queried Bilateral Correlation | |
| CURE | 25.44 | 0.8638 | Learning Cross-Video Neural Representations for High-Quality Frame Interpolation | |
| EBME-H* | 25.40 | 0.863 | Enhanced Bi-directional Motion Estimation for Video Frame Interpolation |
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